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View Code? Open in Web Editor NEWSource code and dataset for NAACL 2019 paper "Adversarial Training for Weakly Supervised Event Detection".
License: MIT License
Source code and dataset for NAACL 2019 paper "Adversarial Training for Weakly Supervised Event Detection".
License: MIT License
您好,请问一下对于Distant Supervision场景时,使用什么做测试集呢?
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您好,我最近也在做事件抽取的工作,但是苦于没有数据集,请问可以发我一份吗?我的邮箱是:[email protected]。非常感谢!
您好,关于论文想请教您一个问题,希望能得到您赐教:
请问文中的Generator选择出困惑度高的实例(selecting the most confusing instances from U to cheat the discriminator)的目的是什么?是为了增强对D的训练(是否能理解为:将G选出的实例作为负例促进D的训练?), 还是理解为过滤掉noisy data减少对D的干扰呢?如果在您的整个系统架构中去掉G, 会有什么影响呢?
初入Event Detection领域,冒昧之处请见谅。期待您的回答,谢谢!
请问是训练和验证的区别吗?
您好,请问您论文中使用的数据划分是什么样子的呢?是否与HMEAE工作中的数据划分保持一致(https://github.com/thunlp/HMEAE/blob/master/logs/split.json )?谢谢
DMCNN是说根据trigger的位置动态的将句子划分成两部分,并通过concat,cnn,进行trigger的分类,那trigger识别是怎么做出来的那?
您好,目前我正在进行事件抽取的项目,需要对数据进行扩充。
浅读了您的论文,发现论文只涉及了事件的类型和触发词,请问能否提取事件的论元呢。
作者你好!
请问在预处理数据的时候,是保留了全部的句子,还是只保留存在event的句子?
谢谢
Line 128 in 60bf954
这一行里面,根据Dscore_G函数的定义,输入参数应该是:
dScores = Dscore_G(nwords, nMask, nmaskL, nmaskR, nlabel,
uwords, uMask, umaskL, umaskR, ulabel)
源代码中的npos,nloc和upos,uloc都没有找到定义
为什么dimE设置为22而不是33那?ACE2005不是规定了33个事件子类型么?
According to part 3.4 of the paper, authors used the small-scale labeled data to train the encoder and discriminator. But what should we do if there is no extra data? Do we need to identify the candidate triggers on dev and test set also?
By the way, since the NYT corpus is really huge, how many sentences did you use for augment data when semi-supervised training ?
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